feat(memory): Day M.1 complete - importance scoring system

- Add FrequencyTracker: increment(), get_frequency_score(), get_recency_score(), get_time_decay()
- Add EmotionAnalyzer: EMOTION_KEYWORDS dict, extract(), calculate_score(), get_emotion_profile()
- Add ImpactEvaluator: evaluate(), get_topic_overlap(), rank_by_impact()
- Add ImportanceScorer: composite scoring (freq 35% + recency 20% + emotion 25% + impact 20%)
- Update UserMemory model: frequency_count, emotion_tags, importance_score, importance_level, associated_topics
- Integrate ImportanceScorer into memory_service.py (recall + importance update)
- Add 37 tests for all memory scoring components
- Fix urgency patterns: remove overly broad '今天' that matched neutral text
- Update memory-update checklist: mark all M.1 tasks complete

backend/app/services/memory_service.py

@@ -7,6 +7,7 @@ Jarvis 记忆系统 (基于 Mem0)
 import logging
 import os
 import re
+import json
 from datetime import UTC, datetime
 from typing import Optional, Any
 from sqlalchemy import select, desc, func
@@ -15,6 +16,10 @@ from app.models.conversation import Conversation, Message
 from app.models.memory import UserMemory
 from app.models.user import User
 from app.services.brain_service import BrainService
+from app.services.memory.frequency_tracker import FrequencyTracker
+from app.services.memory.emotion_analyzer import EmotionAnalyzer
+from app.services.memory.impact_evaluator import ImpactEvaluator
+from app.services.memory.importance_scorer import ImportanceScorer
 from app.config import settings as _settings
 
 try:
@@ -312,8 +317,7 @@ def _extract_memory_query_tokens(query: str) -> list[str]:
             tokens.append(stripped_chunk)
             if len(stripped_chunk) > 6:
                 tokens.extend(
-                    stripped_chunk[index:index + 4]
-                    for index in range(len(stripped_chunk) - 3)
+                    stripped_chunk[index : index + 4] for index in range(len(stripped_chunk) - 3)
                 )
 
     return list(dict.fromkeys(tokens))
@@ -344,16 +348,21 @@ async def recall_user_memories(
 
     query_tokens = _extract_memory_query_tokens(query)
     statement = select(UserMemory).where(UserMemory.user_id == user_id)
-    result = await db.execute(statement.order_by(UserMemory.importance.desc(), UserMemory.created_at.desc()))
+    result = await db.execute(
+        statement.order_by(UserMemory.importance_score.desc(), UserMemory.created_at.desc())
+    )
     fallback_memories = list(result.scalars().all())
 
-    if _contains_hint(_normalize_query(query), MEMORY_QUERY_HINTS) or _matches_memory_query_pattern(_normalize_query(query)):
+    if _contains_hint(_normalize_query(query), MEMORY_QUERY_HINTS) or _matches_memory_query_pattern(
+        _normalize_query(query)
+    ):
         return fallback_memories[:top_k]
 
     if query_tokens:
         matched_memories = [
-            memory for memory in fallback_memories
-            if any(token in (memory.content or '').lower() for token in query_tokens)
+            memory
+            for memory in fallback_memories
+            if any(token in (memory.content or "").lower() for token in query_tokens)
         ]
         return matched_memories[:top_k]
 
@@ -361,13 +370,25 @@ async def recall_user_memories(
 
 
 async def _mark_memories_recalled(db: AsyncSession, memories: list[UserMemory]) -> None:
+    """Mark memories as recalled and update importance score"""
+    from app.services.memory.frequency_tracker import FrequencyTracker
+    from app.services.memory.importance_scorer import ImportanceScorer
+
     recalled_at = datetime.now(UTC)
+    tracker = FrequencyTracker()
+    scorer = ImportanceScorer()
     updated = False
+
     for memory in memories:
         memory.is_recalled = True
         memory.recall_count = (memory.recall_count or 0) + 1
         memory.last_recalled_at = recalled_at
+        memory.frequency_count = memory.recall_count  # Keep in sync
+
+        # Update importance score on recall
+        scorer.update_memory_importance(memory)
         updated = True
+
     if updated:
         await db.commit()
 
@@ -417,9 +438,7 @@ MEMORY_QUERY_HINTS = (
     "偏好",
     "习惯",
 )
-MEMORY_QUERY_PATTERNS = (
-    re.compile(r"\bremember\s+(?:that\s+)?i\b"),
-)
+MEMORY_QUERY_PATTERNS = (re.compile(r"\bremember\s+(?:that\s+)?i\b"),)
 GROUNDING_QUERY_HINTS = (
     "根据文档",
     "严格根据",